Production of natural and recycled aggregates: the environmental impacts of energy consumption and CO<Subscript>2</Subscript> emissions

Natural aggregates (NA) are crushed and processed in crushing plants after the extraction stage in quarries. In the present study, the aggregates are divided into three scenarios, depending on the production methods. The first scenario considers the production of NA, the second scenario deals with the production of recycled aggregates (RA) with respect to construction and demolition waste, and the third scenario, which is a hybrid scenario, handles the combination of NA and RA by assuming a 50% mixing percentage. In this research, we assess the environmental impacts on the production of aggregates via each scenario, using life cycle assessment; in addition, energy consumption and CO₂ emissions are considered as the environmental variables. We conclude that Iran’s current policy with an annual energy consumption of 1.48 million tons of oil equivalent (toe) can have a footprint of 2.88 million tons of CO₂ eq emissions per year (the first scenario). Achieving 30 and 36% reduction in annual energy consumption and CO₂ emissions, respectively, by the third scenario compared to the first scenario indicates the destructive effect of the first scenario from the environmental outlook.     

Space-time stick-breaking processes for small area disease cluster estimation

We propose a space-time stick-breaking process for the disease cluster estimation. The dependencies for spatial and temporal effects are introduced by using space-time covariate dependent kernel stick-breaking processes. We compared this model with the space-time standard random effect model by checking each model’s ability in terms of cluster detection of various shapes and sizes. This comparison was made for simulated data where the true risks were known. For the simulated data, we have observed that space-time stick-breaking process performs better in detecting medium- and high-risk clusters. For the real data, county specific low birth weight incidences for the state of South Carolina for the years 1997–2007, we have illustrated how the proposed model can be used to find grouping of counties of higher incidence rate.     

Nano-sized Prussian blue immobilized costless agro-industrial waste for the removal of cesium-137 ions

Environmental Science and Pollution Research - For human health and safety, it is of great importance to develop innovative materials with a vast capacity for powerful removal of radioactive ions...     

Graphene Oxide Caged Biopolymer Nanocomposite for Purification of Rare Earth Elements from High Grade Egyptian Monazite Concentrate

Journal of Polymers and the Environment - Rare earth elements (REEs) play a critical role in the applications of advanced materials. In this respect, an eco-friendly calcium/alginate-graphene oxide...     

Local likelihood disease clustering: development and evaluation

This paper illustrates a method based on local likelihood (LL) for detecting disease clusters. The approach is based on estimating a lasso distance for each region: within which regions are considered to be clustered. An important advantage in implementing this approach is that it does not require any special Monte Carlo Markov Chain (MCMC) algorithm, e.g., reversible jump MCMC, which is essential in hidden Markov model approach. Another advantage is that extending the model to incorporate covariates is straightforward. We illustrate three ways of doing this by using Eastern Germany lip cancer data. By using simulated data, we have made a comparison with the BYM model [Besag et al. (1991) Annals of the Institute of Statistical Mathematics, 43, 1–59] and the mixture model [Lawson and Clark (2002) Disease Mapping and Risk Assessment for Public Health, Chapman and Hall]. We also did a limited examination of the ability of the LL model to recover true relative risk under different priors for lasso parameter. In order to check the edge effects, which has been overlooked in many spatial clustering models for disease mapping but deserves special attention as it lacks observable neighbors, we have adapted here a simple approach to observe the changes in relative risks when the edge regions are omitted. An erratum to this article is available at .     

Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detection

This paper extends the spatial local-likelihood model and the spatial mixture model to the space-time (ST) domain. For comparison, a standard random effect space-time (SREST) model is examined to allow evaluation of each model’s ability in relation to cluster detection. To pursue this evaluation, we use the ST counterparts of spatial cluster detection diagnostics. The proposed criteria are based on posterior estimates (e.g., misclassification rate) and some are based on post-hoc analysis of posterior samples (e.g., exceedance probability). In addition, we examine more conventional model fit criteria including mean square error (MSE). We illustrate the methodology with a real ST dataset, Georgia throat cancer mortality data for the years 1994–2005, and a simulated dataset where different levels and shapes of clusters are embedded. Overall, it is found that conventional SREST models fair well in ST cluster detection and in goodness-of-fit, while for extreme risk detection the local likelihood ST model does best.     

Elucidation of ecosystem attributes of an oligotrophic lake in Hokkaido,Japan, using Ecopath with Ecosim (EwE)

The fishing practices in the oligotrophic Lake Toya, Hokkaido, Japan, have profound implications in the ecosystem sustainability. The status of the sockeye salmon (Oncorhynchus nerka) population has become a serious concern among the lake managers and policy makers during the last decades. While the decline of the sockeye salmon population has been well documented in Lake Toya, there is considerable uncertainty with regards to the impact on the broader system dynamics. In this study, our objective is to address this knowledge gap by undertaking a synthesis of the Lake Toya food web using the mass-balance modeling software Ecopath with Ecosim (EwE). Our primary research question is to examine the repercussions of the declining sockeye salmon population on the trophic dynamics of the lake. Namely, we assess if there are any competing species that might have benefited from the decrease of sockeye salmon standing biomass and to what extent do these changes propagate through the Lake Toya food web? Our analysis pinpoints the critical role of the Japanese smelt (Hypomesus transpacificus nipponensis) in the system, which demonstrates a wide range of effects on several functional groups at both higher and lower trophic levels in Lake Toya. In particular, being a substantial portion of the masu salmon (Oncorhynchus masou) and adult sockeye salmon diets, the Japanese smelt has a positive impact on the top predators of the system. Amphipods, insects, and shrimp strongly benefit from the autochthonous and allochthonous organic matter in the system, while the tight coupling between phytoplankton and zooplankton seems to be particularly critical for the integrity of the Lake Toya food web. Whereas the values of the different ecosystem attributes (e.g., primary production/biomass, biomass/total throughput, system omnivory index, amount of recycled throughput, Finn's cycling index) provide evidence that Lake Toya is an immature system, we note that the internal redundancy and the system overhead estimates suggest that the lake possesses substantial reserves to overcome external perturbations. We also examined the effects of a variety of fishing policies on the biomass of masu salmon and adult sockeye salmon, which verify the belief that the adult sockeye population is quite fragile with high likelihood to collapse. Our analysis also predicts that sockeye will not rebound unless the fishing pressure exerted is substantially reduced (>50% of the reference levels used). Masu salmon seems to benefit under all the scenarios examined indicating that the intensity of the current fishing activities is significantly lower than its biomass accumulation rate in the system.